Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/455416
Title: | Artificial Neural Network Based Diagnostic Model for the Early Detection of Disease |
Researcher: | Dikshit, Geetika |
Guide(s): | Tiwari, Ravindra Kumar |
Keywords: | Computer Science Computer Science Interdisciplinary Applications Engineering and Technology |
University: | LNCT University |
Completed Date: | 2022 |
Abstract: | In present times, In the Field of healthcare Identification of Heart Disease is difficult. Just because of this heart disease, around one person passes away per minute in modern era. There is a requirement of automation of prediction system to avoid hazard related with it as well as aware the patient s health in advance. There are various ML techniques has been exposed to be helpful in supporting, predictions and making decisions from the huge data which is generated through the medical industries. In this article, we offer a new system that intend to focus on important features through concerning machine learning methods that resultant in improve the accurateness within the heart disease prediction. The proposed model is established by special feature s combinations and numerous recognized classification methods. We generate an improved performance level through an above 80% accuracy level throughout the proposed model intended for heart disease prediction system by the hybrid model. Therefore, this article represents a relative learning by evaluate the performance of various machine learning techniques. newline |
Pagination: | |
URI: | http://hdl.handle.net/10603/455416 |
Appears in Departments: | Department of Computer Science and Application |
Files in This Item:
File | Description | Size | Format | |
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10_chapter 7.pdf | Attached File | 17.84 kB | Adobe PDF | View/Open |
12_abstract.pdf | 53.35 kB | Adobe PDF | View/Open | |
13_contents.pdf | 120.4 kB | Adobe PDF | View/Open | |
1_title.pdf | 25.27 kB | Adobe PDF | View/Open | |
2_certificate.pdf | 48.5 kB | Adobe PDF | View/Open | |
3_declaration.pdf | 9.58 kB | Adobe PDF | View/Open | |
4_chapter 1.pdf | 853.38 kB | Adobe PDF | View/Open | |
5_chapter 2.pdf | 765.72 kB | Adobe PDF | View/Open | |
6_chapter 3.pdf | 546.57 kB | Adobe PDF | View/Open | |
7_chapter 4.pdf | 714.66 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 32.93 kB | Adobe PDF | View/Open | |
8_chapter 5.pdf | 78.16 kB | Adobe PDF | View/Open | |
9_chapter 6.pdf | 450.68 kB | Adobe PDF | View/Open | |
references.pdf | 157.83 kB | Adobe PDF | View/Open |
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